The seasonality of cholera in sub-Saharan Africa: a statistical modelling study. Issue 6 (June 2022)

• Record Type: Journal Article
• Authors: Perez-Saez, Javier; Lessler, Justin; Lee, Elizabeth C; Luquero, Francisco J; Malembaka, Espoir Bwenge; Finger, Flavio; Langa, José Paulo; Yennan, Sebastian; Zaitchik, Benjamin; Azman, Andrew S
• Is Part Of: Lancet. Volume 10:Issue 6(2022)
• Page Start: e831
• Page End: e839
• Publication Date: 2022-06
• Subjects: World health -- Periodicals; 362.105
• DOI: 10.1016/S2214-109X(22)00007-9
• Languages: English
• ISSNs: 2214-109X

Abstract

Summary: Background: Cholera remains a major threat in sub-Saharan Africa (SSA), where some of the highest case-fatality rates are reported. Knowing in what months and where cholera tends to occur across the continent could aid in improving efforts to eliminate cholera as a public health concern. However, largely due to the absence of unified large-scale datasets, no continent-wide estimates exist. In this study, we aimed to estimate cholera seasonality across SSA and explore the correlation between hydroclimatic variables and cholera seasonality. Methods: Using the global cholera database of the Global Task Force on Cholera Control, we developed statistical models to synthesise data across spatial and temporal scales to infer the seasonality of excess (defined as incidence higher than the 2010–16 mean incidence rate) suspected cholera occurrence in SSA. We developed a Bayesian statistical model to infer the monthly risk of excess cholera at the first and second administrative levels. Seasonality patterns were then grouped into spatial clusters. Finally, we studied the association between seasonality estimates and hydroclimatic variables (mean monthly fraction of area flooded, mean monthly air temperature, and cumulative monthly precipitation). Findings: 24 (71%) of the 34 countries studied had seasonal patterns of excess cholera risk, corresponding to approximately 86% of the SSA population. 12 (50%) of these 24 countries also had subnational differences in seasonality patterns, with strong differences in seasonality strength between regions. Seasonality patterns clustered into two macroregions (west Africa and the Sahel vs eastern and southern Africa), which were composed of subregional clusters with varying degrees of seasonality. Exploratory association analysis found most consistent and positive correlations between cholera seasonality and precipitation and, to a lesser extent, between cholera seasonality and temperature and flooding. Interpretation: Widespread cholera seasonality in SSA offers opportunities for intervention planning. Further studies are needed to study the association between cholera and climate. Funding: US National Aeronautics and Space Administration Applied Sciences Program and the Bill & Melinda Gates Foundation.